Bibliographic record
Abstract
The first local exchange trading system(LETS), established in Comox Valley in Canada, aimed at facilitating the regional economy. However, in Korea, LETS was adopted to encourage mutual aid and promote community spirit among residents. This study examines the feasibility of LETS as a revitalization initiative for Pumasi and suggests a number of policies that can be implemented to support the project. The findings are as follows: First, the LETS credit system was found to complement social capital initiatives among Pumasi participants in the early stages of the Pumasi project. Second, combining LETS and Pumasi initiatives was found to consolidate community spirit and encourage a cooperative way of life among participants due to the fact that LETS enlarges the scope of local residents’ participation and diversifies the services being exchanged. A number of policy suggestions are made for combining LETS with Pumasi. First, the project must define a vision of its long-term purpose and outcomes. Second, local residents should be employed as assistants to facilitate the project. Third, Pumasi participants should ensure that childcare exchange services are of the highest quality by providing an educational program on parenting. Fourth, the project manager's employment conditions and working environments must be guaranteed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".